In recent years, energy harvesting has attracted significant attention in order to prolong the lifetime of remote devices [1]}, [2]}, [3]}. Energy can be harvested from different sources like wind, thermal, solar, and wireless radio-frequency (RF), but the efficiency of each method depends on its availability. RF signals are accessible in various environmental conditions; hence, it is appropriate to be utilized in IoT applications [4]}. Another crucial concern in IoT applications is the availability of frequency spectrum. Recently, cognitive radio networks (CRNs) have been proposed to solve this problem [5]}. Cognitive radio can be adopted in various networks to enhance the efficiency of the spectrum and improve the performance of the system [3]}, [7]}, [8]}.
By adopting energy harvesting in CRNs, we can simultaneously exploit the advantages of energy harvesting and cognitive radio. This kind of network is called energy harvesting CRNs (EH-CRNs) [8]}. In the EH-CRNs, all secondary users (SUs) are battery-free and could be equipped with a super-capacitor that can keep harvested energy temporarily due to its high rate of self-discharge characteristic [10]}. Therefore, each SU can harvest energy just prior to the transmission mode. This method is known as harvest-then-transmit (HTT).
